Russell Parrott is an independent author and researcher working on AI governance, structural accountability, technological power and institutional resilience.
He develops and publishes original reference standards, governance tests and analytical frameworks concerned with whether AI systems can demonstrate control, traceability, accountability and resilience in practice.
His wider work examines the consequences of artificial intelligence, including the changing balance of power between governments and corporations, AI sovereignty, geopolitical dependency, energy and infrastructure, and the implications of increasingly privatised intelligence systems.
His publications include the Standardized Definition of AI Governance, the Evidential Resilience Ratio (ERR),the External AI Withdrawal and Geopolitical DisruptionTest and The AI World Order: Intelligence, Power and the Global Conflict.
His research and reference work is published independently through Zenodo and other public repositories, where it is versioned, citable and open to scrutiny. He does not provide consultancy or advisory services.
Writing is his profession. Using the pen name Cecil Atley he also writes the Rhys Maren historical mysteries, which centre on evidence, forgotten histories and the reconstruction of events from records left behind.
A public reference standard that defines AI governance as a measurable structural condition, moving beyond policy statements to test whether control, accountability, traceability and integrity can be demonstrated in practice across the AI lifecycle.
A quantitative AI governance metric designed to measure how much of an AI system remains provable when models, APIs, vendors or other upstream dependencies change. ERR focuses on traceability, reconstructability, version fidelity and dependency proof to assess whether governance can survive change.
A practical governance test examining whether a business can maintain critical services if access to an external AI provider is suddenly restricted or withdrawn because of provider decisions, government action, sanctions, trade restrictions or geopolitical disruption.
A public reference framework for testing whether important AI protections actually work in practice, focusing on control, accountability, business dependence and effective oversight rather than relying on policies, promises or formal safeguards alone.
The Standardized Definition of AI Governance provides the foundation. It sets out what AI governance should mean in practice and how it can be tested, rather than relying only on policies, principles or statements of intent. Its focus is on whether control, accountability, human oversight, traceability and wider governance structures can actually be demonstrated.
The Evidential Resilience Ratio (ERR) and the External AI Withdrawal and Geopolitical Disruption Test then address two specific areas that broader governance frameworks may leave to implementation.
ERR focuses on evidence and auditability: if the technology changes, can the organisation still prove what happened? The External AI Withdrawal and Geopolitical Disruption Test focuses on dependency and continuity: if an external AI service is restricted, withdrawn or becomes unavailable can the organisation still operate?
Together, the three provide practical structural tests and measurements for turning broad AI governance requirements into questions that organisations can actually examine, evidence and act on.